Category Archives: American Community Survey

Examining America’s Cities: Demographic-Economic Updates

.. of the approximate 29,500 U.S. cities and places — geographic areas of population concentration — 301 had an ACS 2016 5-year estimated population of 100,000 or more. The median household income among these places, one measure of economic prosperity, ranged from $26,249 (Detroit, MI) to $117,642 (Frisco, TX).

What are the demographic-economic characteristics of your cities/places of interest? How do these compare to peer groups or a metro/state of interest. Learn more using the new city/place demographic interactive tables. Its about more than economic prosperity — using these data provide otherwise unknowable attributes about the demographic, social, economic and housing characteristics of individual cities/places.

Visual Analysis of City/Place Population Dynamics
The following view shows patterns of population percent change by city in the Charlotte, NC/SC metro area.

… view developed using the CV XE GIS software.
… more about above view in City/Place Economic Characteristics section.

Patterns of Economic Prosperity ($MHI) by City/Place
— Northern Virginia, DC, Maryland; part of the Washington, DC metro.

… view developed using the CV XE GIS software.
… click graphic for larger view with places labeled by name and $MHI.

Interactive Tables — new January 2018
Use these interactive tables to get answers, build insights:
• General Demographics
• Social Characteristics
• Economic Characteristics — used to develop data at top of section
• Housing Characteristics
Related:
• City/Place GeoDemographics Main Section
• Annual City/Place Population Estimates & Trends
• Similar ACS tables: Census Tracts | ZIP Codes | State, Metro & County

More About City/Place GeoStatistical Data and Data Analytics
The term “places” as used here refers to incorporated places and Census Designated Places (CDPs). Incorporated places are political areas having certain governmental powers designated by the corresponding state. Unincorporated places, or Census Designated Places (CDPs), are statistical areas having no official standing and no governmental powers but are recognized as being areas of population concentration. Wide-ranging demographic-economic estimates are developed annually for the approximate 29,500 incorporated cities and CDPs based on the American Community Survey 5-year estimates. See more about the ACS 2016 5-year estimates.

Many cities have planning and data development operations that develop important local data including tax parcel data, building permit data, transportation and infrastructure data … bit generally not the data reviewed in this section. Many cities have no planning department to develop, organize and analyze geographic, demographic, economic data … making these data even more essential.

Increasingly in core sections of metropolitan areas, as shown in the above graphics, a large number of cities/places are contiguous. Many retain their own character evolving over many years. Having the detailed ACS demographic-economic data makes it possible to compare places side by side. Use the same data for related drill down geography such as census tracts and block groups to examine neighborhoods and market areas.

Data Analytics Web Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Metro 2016 Demographic-Economic Data Analytics: Social Characteristics

.. part one of four parts focused Metro 2016 Demographic-Economic Data Analytics.  This post is on Social Characteristics; ahead: general demographics, economic characteristics and housing characteristics. See related Web section.

Patterns of Educational Attainment by Metro
The following graphic shows patterns of educational attainment (percent college graduate) by Metropolitan Statistical Area (MSA). Legend shows color patterns associated with percent college graduate values.

– View developed using CV XE GIS software and associated GIS project.
– use these resources to develop similar views for any area.
– modify subjects, zoom, colors, labels, add your data.

A Selected Social Characteristic & How Metros Vary
In 2016, the U.S. percent college graduates was 31.3 percent (of the population ages 25 and over) while Metropolitan Statistical Areas (MSAs) ranged from 11.3% (Lake Havasu City-Kingman, AZ MSA) to 60.6% (Boulder, CO MSA). See item/column S067 in the interactive table to view, rank, compare, analyze metros based on this measure for 2016 … in context of related social characteristics. These data uniquely provide insights into many of the most important social characteristics.

Social Characteristics – Subject Matter Covered
– Households by Type
– Relationship
– Marital Status
– Fertility
– Grandparents
– School Enrollment
– Educational Attainment
– Veteran Status
– Disability Status
– Mobility; Residence 1 Year Ago
– Place of Birth
– Citizenship Status
– Year of Entry
– Region of Birth
– Language Spoken at Home
– Ancestry
– Computers & Internet Use

Metro Data Analytics
Use tools, resources and methods to access, integrate and analyze social characteristics for metropolitan areas or Core-Based Statistical Areas (CBSAs). The table includes data for 382 Metropolitan Statistical Areas (MSAs) and 129 Micropolitan Statistical Areas (MISAs). These data will update in September 2018.

Approximately 600 subject matter items from the American Community Survey ACS 2016 database (released September 2017) are included in these four pages/tables:
• General Demographics
• Social Characteristics — reviewed here
• Economic Characteristics
• Housing Characteristics
See related Metro Areas Population & Components of Change time series data.

Focusing on Specific Metros & Integrated Multi-sourced Data
While these data provide a good cross section of data on social characteristics, this access structure is a) for one time period and b) data sourced from one statistical program. Also, there is a lot going on in metros; these are typically large areas with many important and diverse smaller geographies such as cities, counties and neighborhoods among other others.

Use the Metropolitan Situation & Outlook (S&O) reports to develop extended insights. See this example of the Washington, DC MSA S&O Report. Examine trends and projections to 2030. Inegrate your own data.

Using the Interactive Table
The following example illustrates use of the metro social characteristics interactive table … try using it on areas of interest. This view, showing metros partly or entirely in Arizona, was first developed by using the state selection tool below the table Next the selected columns button the table is used to examine educational attainment columns/items. The final step was to click the header cell on the “S067” item to sort metros on percent college graduates. It is easy to determine that the Flagstaff metro has the highest percent college graduates (home to Northern Arizona University).

Data Analytics Web Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Federal Statistical System Updates January 2018

.. sharing updates on developments about and within the Federal Statistical System (http://proximityone.com/fss.htm). Today I attended a briefing by Nancy Potok, U.S. Chief Statistician (part of OMB OIRA) at the American Statistical Association offices. The session was coordinated by the Council of Professional Associations on Federal Statistics (COPAFS).

Several topics were discussed, including:

1. Will the Federal government shutdown on January 19, 2018, due to a budget impasse? As of now, there seems to be a 50-50 consensus likelihood.

2. In the spring of 2018, there might be a far-reaching Federal government reorganization plan released by OMB. While there are no details on this, it may well be that certain Federal statistical agencies will be reorganized. This follows more than a year of processing recommendations suggested by individual agencies. Right now, it is not clear if this will be focused on Federal statistical and information-related operations or something broader.

3. It is expected that the 2018 Federal budget, thus including the 13 primary Federal statistical agencies, will be released in early February. Much of the 2019 Federal budget is also completed, though many important details remain.

4. The widely publicized possible addition of a citizenship question to 2020 census questionnaire was discussed. OMB approves the addition or deletion of all questions on Federal government information collection forms. See USATODAY editorial comments today, consistent with my opinion. The merit to the argument to add the citizenship question, if there is one, is that while block group level tabulations of citizenship status from the American Community Survey are available and updated annually, these are subject to sampling error and other errors of estimation, they are not tabulated at the census block level, they are estimates for respondents over a five year period, and they will lag the 2020 census data (first release March 31, 2021) with ACS 2018 estimates (centric to mid-2016) released in December 2020. Key facts are that 1) at there is no Federal government agency requirement for citizenship by block data, 2) a citizenship question definitely imperil the quality of the Census 2020 results, 3) block group level data are sufficient for any reasonable need, 4) the cost of adding the question would be huge in an already underfunded census.

Next Federal Statistical System Updates
The next planned Federal Statistical System update will be in March followed by an update in April. We might move to a recurring monthly update.

Data Analytics Web Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Congressional District/State Legislative District Data Analytics Sessions

.. join me in the Congressional District/State Legislative District Data Analytics Sessions .. http://proximityone.com/cdsld/cdsld_vasessions.htm .. face-to-face sessions in the Washington, DC area.

Legislative Districts & Patterns of Neighborhood Economic Prosperity
Census tracts labeled with median household income in context VA House District 11 (bold blue boundary) in Fairfax County, VA. Use the GIS project to examine any state legislative district.

— click for larger view
— view created using CV XE GIS & associated GIS project.

CDSLD Sessions These sessions are focused on tools, data and analytical methods relating to Congressional Districts (115th CDs) and State Legislative Districts (2016 cycle SLDs). We focus on national and Virginia CDs and SLDs in context of the total population, voting population, the Citizen Voting Age Population characteristics and patterns with drill down to census blockblock groupcensus tractelection precinctcity/placeZIP codecountymetro and other geography.

Program details as PDF: http://proximityone.com/cdsld/cdsld_vasessions.pdf.

Anyone may attend. There is no fee. There is no promotional content. Sessions are presented by Warren Glimpse an expert on the topics covered. Learn more about the potentials of using these tools, data and methods. Get answers to your questions to learn more about what data are available, options to access the data, how to integrate these data with other data and insights into how you can use and the data. Attend one or many sessions. While there are core topics, new related material and updates are covered in each session. Join in as a continuing program. Develop and extend data analytics skills.

Patterns of Economic Prosperity by VA Senate District
– Virginia Upper/Senate SLDs by Median Household Income

– click graphic for better quality view; districts labeled with district code

More About Congressional Districts & State Legislative Districts
See the related section for more information:
• 115th Congressional Districts ..
.. Main .. http://proximityone.com/cd115.htm
.. demographic-economic tables http://proximityone.com/cd161dp1.htm
• State Legislative Districts Main .. http://proximityone.com/sld2016.htm
.. with demographic-economic interactive table
• Virginia State Legislative Districts .. http://proximityone.com/sld_va.htm
.. interactive table with incumbency details

CDSLD Data Analytics Web Sessions
Unable to join the face-to-face session? Join me in a Data Analytics Web session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Examining America’s 10 Largest Urban Areas

.. why it matters .. among other reasons, these 10 areas have 24% of the total U.S. population. Three have increased by more than 20% in the past 5 years.

More than 80-percent of America’s population is urban, but far more than 80-percent of America’s geography is rural. Census 2010 shows that America’s urban population increased by 12.1 percent from 2000 to 2010, compared to the national overall growth rate of 9.7 percent. Urban areas now account for 80.7 percent of the U.S. population, compared to 79.0 percent in 2000.

America’s 10 Largest Urbanized Areas
The following table shows the largest 10 Urbanized Areas (UAs) based on the American Community Survey 2011 and 2016 1-year estimates (ACS2016) and change over the period. UAs are sorted in descending order based on the 2016 population estimate. Note that Atlanta, Dallas and Houston moved up in rank.

Geodemographic relationships vary widely between the urbanized areas (UAs). Some, such as Miami, comprise most or all of the urban area within the corresponding metropolitan statistical area. Others, such as Philadelphia, are nested within a mix of adjacent urban areas interspersed with rural areas. Among other things, these different geodemographic structures reflect how planning, needs assessment and market development vary widely from associated metro-to-metro. These data show the importance and need to consider the urban/rural population distribution even in the largest metros.

Visual Analysis — Dallas Urbanized Area
The urbanized area (UA) of the corresponding metropolitan statistical area (MSA) generally occupies less than half of the MSA.
See the Dallas-Fort Worth-Arlington, TX MSA Situation and Outlook Report

… View developed using CV XE GIS.

Map Views for Each of the Largest 10 Urbanized Areas
Maps for each of the 10 largest UAs are shown at
http://proximityone.com/urbanareas_2016.htm.

Each graphic shows the designated urbanized area in a darker salmon color fill pattern, associated metropolitan statistical area with bold brown boundary, and other urban areas with a lighter shade of salmon fill color, counties black boundaries and yellow labels. The ACS 2016 UA population is shown as a white label under the UA name. The ACS 2016 estimates are the most recent data available and will update with 2017 estimates in late 2018.

More About Analyzing Urban/Rural Patterns and Characteristics
See the related section on America’s urban/rural population and geography:
http://proximityone.com/urbanpopulation.htm.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on L

Creating Custom Demographic Datasets with API Tools

.. develop national scale spreadsheet files with virtually no learning time .. easy-to-use API operations to create national scope demographic-economic datasets based on American Community Survey 2016 1-year estimates .. custom subject matter selections. See more detail in related web sections ACS2016 and ACS2016_API.

Benefits and utility … how to acquire a spreadsheet showing the population of all cities with population estimates based on the ACS 2016 1-year data? … or, housing units, median household income, median housing value, etc.? Variations of this need frequently arise — what is the list of largest California counties sorted on total population: What are the 25 metros having the highest median household income? Which 10 congressional districts have the highest poverty incidence? Which urban areas have the highest educational attainment?

Use simple API calls described below to get answers to these types of questions — and more.  Create files that can be used for recurring applications. An example …

Urban Areas with 2016 Population 65,000+ Population
… results from using the API downloaded data … the following graphic shows urban areas with 65,000 or more 2016 population; zoom-in to Texas. The full national scope GIS project is available as described below; examine U.S. or any region. The file used to develop this view was created using the results of the API call reviewed below (requires integration of those data into the urban areas shapefile). Click graphic for larger view; expand browser window. Larger view shows urban areas labeled with name and mini profile for Dallas UA showing all subject matter items downloaded (via API) as described below.

… View developed using CV XE GIS.
… See more about Urban Population & Urban Areas.

Access ACS 2016 1-Year Data Using API Tools
Here are the API links … use these API calls to access/download selected items for selected geographies. See more about using API tools. Click a link and receive a return page with CSV-like structured data. See usage notes below. As these are ACS 2016 1 year estimates; geographies are only available for areas 65,000+ population.
Click a link:
• All U.S. cities/places
• All U.S. counties
• All U.S. CBSAs
• All U.S. Urban Areas
• All 115th Congressional Districts
• All U.S. states
• U.S. only

The following data retrieval operations are by state. These are examples using Arizona (FIPS state code 04).
• All [within state] Elementary School Districts
• All [within state] Secondary School Districts
• All [within state] Unified School Districts

API Call Returned Data Usage Notes
Clicking the All U.S. cities/places link above generates a new page with content very much like a CSV file. Try it .. click an above link.

See the related ACS2016_API web section for more details.

Items Retrieved in the API Calls
The sample header record above shows the subject matter item listed at the left in the following set of items. Modify API call and use other subject matter items. See full array of subject matter – xlsx file.
.. B01003_001E – Total population
Age
.. B01001_011E — Male: 25 to 29 years (illustrating age cohort access)
.. B01001_035E — Female: 25 to 29 years (illustrating age cohort access)
Race/Origin
.. B02001_002E – White alone
.. B02001_003E – Black or African American alone
.. B02001_004E – American Indian and Alaska Native alone
.. B02001_005E – Asian alone
.. B02001_006E – Native Hawaiian and Other Pacific Islander alone
.. B02001_007E – Some other race alone
.. B02001_008E – Two or more races
.. B03001_003E – Hispanic (of any race)
Income
.. B19013_001E – Median household income ($)
.. B19113_001E – Median family income ($)
Housing & Households
.. B25001_001E – Total housing units
.. B25002_002E – Occupied housing units (households)
.. B19001_017E — Households with household income $200,000 or more
.. B25003_002E — Owner Occupied housing units
.. B25075_025E — Housing units value $1,000,000 to $1,499,999
.. B25075_026E — Housing units with value $1,500,000 to $1,999,999
.. B25075_027E — Housing units with value $2,000,000 or more
.. B25002_003E – Vacant housing units
.. B25077_001E – Median housing value ($) – owner occupied units
.. B25064_001E – Median gross rent ($) – renter occupied units

The rightmost fields/columns in the rows/records contain the area name and geographic codes.

Using API Tools for Data Analytics
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on L

State of the States: Demographic Economic Update

.. tools and resources to examine the demographic-economic state of the states .. in 2016, the U.S. median housing value was $205,000 while states ranged from $113,900 (Mississippi) to $592,000 (Hawaii). See item/column H089 in the interactive table to view, rank, compare, analyze state based on this measure … in context of related housing characteristics. These data uniquely provide insights into many of the most important housing characteristics.

Use new tools, data and methods to access, integrate and analyze demographic-economic conditions for the U.S. and states. These data will update in September 2018.

Approximately 600 subject matter items from the American Community Survey ACS 2016 database (released September 2017) are included in these four pages/tables:
• General Demographics
• Social Characteristics
• Economic Characteristics
• Housing Characteristics

GIS, Data Integration & Visual Data Analysis
Use data extracted from these tables in a ready-to-use GIS project. These ACS sourced data (from the four tables listed above) have been integrated with population estimates trend data, components of change and personal income quarterly trend data. See details in this section.

Examining Characteristics & Trends
Below are four thematic pattern maps extracted from the main sections listed above. Click a map graphic for a larger view. Use the GIS project to create variations of these views.

Patterns of Median Age by State
Yellow label shows the state USPS abbreviation; white label shows median age. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column D017 in the interactive table to view, rank, compare, analyze state based on median age.

Patterns of Educational Attainment by State
Yellow label shows the state USPS abbreviation; white label shows % college graduates. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column S067 in the interactive table to view, rank, compare, analyze state based on percent college graduates.

Patterns of Economic Prosperity by State
Yellow label shows the state USPS abbreviation; white label shows $MHI. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column E062 in the interactive table to view, rank, compare, analyze state based on median household income.

Patterns of Median Housing Value by State
Yellow label shows the state USPS abbreviation; white label shows $MHV. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column H089 in the interactive table to view, rank, compare, analyze state based on median housing value.

Examining Characteristics & Trends; Using Data Analytics
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.